I took a quick look at your images. For most of them, the crosscovariances are near 0 (or even negative) for short distances. This implies that there is little correlation between the variables. The idea is that for short distances, the variables should have high crosscovariance (indicating that they are correlated). This covariance should decrease as the distance increases until they level out near zero (which indicates that they are no longer correlated). You need to try to identify the distance where these covariances generally become zero. However, it isn't clear to me from those pictures if there is any crosscovariance between the variables at all.
You may be able to better identify the distance you need in the Geostatistical Wizard. Perform cokriging, and look at the crosscovariance view on the semivariogram page. This graph won't have as many points as the cloud, and it will try to fit a covariance model automatically. Whatever Major Range is estimated should be a good estimate of the range of crosscovariance between the variables.
